Corpus-based approaches to machine translation usually begin with a bilingual training corpus. One approach is to extract from the corpus generalized statistical knowledge that can be applied to new, unseen test sentences. A different approach is to simply memorize the bilingual corpus. This is called translation memory, and it provides excellent translation quality in the case of a “hit” (i.e., a test sentence to be translated has actually been observed before in the memorized corpus). However, it provides no output in the more frequent case of a “miss”.